medlid-identify – AI Model by onionLad | AlphaNeural AI

You can deploy this model and start earning money today!

onionLad/
medlid-identify

like

0

token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

Views

No views yet

medlid-identify

This model is a fine-tuned version of bert-large-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1708
Precision: 0.3912
Recall: 0.4603
F1: 0.4229
Accuracy: 0.9463

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 81
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	381	0.1567	0.2689	0.3180	0.2914	0.9377
0.1618	2.0	762	0.1399	0.4016	0.3847	0.3930	0.9492
0.0978	3.0	1143	0.1505	0.3773	0.4239	0.3993	0.9468
0.0636	4.0	1524	0.1708	0.3912	0.4603	0.4229	0.9463

Framework versions

Transformers 4.30.2
Pytorch 1.11.0
Datasets 2.13.1
Tokenizers 0.13.3